@article{scholars11735,
            year = {2019},
           pages = {24--35},
         journal = {Chemical Engineering Research and Design},
       publisher = {Institution of Chemical Engineers},
             doi = {10.1016/j.cherd.2019.01.001},
            note = {cited By 3},
          volume = {143},
           title = {A mixed integer nonlinear programming approach for petroleum refinery topology optimisation},
        abstract = {This work presents a mixed integer nonlinear programming (MINLP)-based superstructure optimisation approach to synthesize an optimal petroleum refinery topology or configuration for large-scale grassroots refinery systems. We develop a superstructure to include many possible prospective configurations and formulate rigorous models for the 32 commercial refinery processes that constitute the configurations, which gives rise to a convex MINLP model. The objective function is to maximize the total refinery profit for a given crude oil feed subject to material and energy balance constraints. We apply a two-level optimisation procedure: a master module to construct configurations from the superstructure and a submodule to optimize the process unit conversions and product temperatures of the configurations. A numerical example based on an actual operating refinery in Kuwait is illustrated to implement the approach with a resulting configuration that agrees with real-world practices. {\^A}{\copyright} 2019 Institution of Chemical Engineers},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060245438&doi=10.1016\%2fj.cherd.2019.01.001&partnerID=40&md5=daab624bd25f1ddfec6c27743ad26248},
        keywords = {Fluid catalytic cracking; Gasoline; Integer programming; Nonlinear programming; Structural optimization; Topology, Atmospheric residues; Fluid catalytic crackers; Parameter optimisation; Process synthesis; Topology optimisation; Vacuum residue, Petroleum refineries},
          author = {Albahri, T. A. and Khor, C. S. and Elsholkami, M. and Elkamel, A.},
            issn = {02638762}
}